Project 1: How People’s Travel Destinations Change with Pandemic Phases

1 Introduction

1.1 BACKGROUND

1.1.1 Rail Ridership: Correlated to Urban Development

Rail network is the backbone of the public transport system in Singapore. The first MRT section was opened in November 1987 (Xuan Zhu et al., 2004). According to LTA (2013), the rail network will be expanded to about 360 km by 2030 from 200 km in 2020. This means connecting eight in 10 households to within 10 minutes of a train station.

Ridership, or passenger volume, is one of the most commonly used measures to capture the effect of the surrounding land use, clustered development, diversity, density, transit supply, system efficiency on transit use (Chakraborty & Mishra, 2013). Higher ridership also reveals higher popularity and better economic benefits.

The difference in land use allocation has an effect on the popularity of rail stations. As Xuan Zhu et al. (2004) mentioned, the existing urban land use configuration helps to shape travel patterns. In Singapore, the urban center hierarchy and the new town development concept have led to the difference in land use characteristics of the TOD stations (Shaofei Niu et al., 2019). Many studies did the correlation analysis of ridership data and land use data. Sidek et al. (2017) summarized related papers and concluded that high public transit ridership is related to high land use density. In addition, a diversity of land uses among three major categories within the walking radius of the station can also accumulate transit passenger volume. Kim et al. (2017) used transit smart card data to identify the travel pattern and reveal the relationship between travel patterns and the surrounding environment in Seoul. Through quantifying linear functions consisting of ridership and GFA, Berawi et al. (2020) found that office development can generate more passengers while residential development can generate less.

1.1.2 The Impact of COVID-19

Pandemic also influences the ridership of public transport. Because of the breakout of COVID-19, the transport sector has experienced a drastic reduction in passenger traffic (Sarbast Moslem et al., 2020). According to LTA (2020), ridership of MRT plummeted by 75 per cent in April compared to pre-COVID levels in Singapore. Singapore exited Circuit Breaker from June 2 June 2020 and started Phase One: Safe Re-opening. Economic activities which do not pose high risk of transition were gradually reopened in this stage, while social, economic and entertainment activities with a higher risk will remain closed. Passenger flow of the railway partly recovered compared with the time during Circuit Breaker. Phase Two of reopening started from 19 June 2020. Certain places for recreation and activities gradually reopened in the late June or early July under strict restrictions. Therefore, passenger flow of many MRT stations increased significantly in July. The Land Transport Authority (LTA) reported on Feb 10, 2021 that average daily ridership for public transportation fell by 34.5 per cent to 5.04 million (11 year low), which broke the trend of consecutive rises in public transportation in the previous 15 years. Work from home induced by Covid-19 led to the reduction of MRT and LRT lines to 2.162 million a day. The reduction in public transport ridership has raised concerns regarding the financial sustainability of the MRT network, which was primarily designed with pre-pandemic usage in mind.(Christopher Tan, 2020) Singapore, with limited land, requires more careful and effective urban planning. The analysis of railway passenger volume can help to understand human mobility, and therefore further understand human daily activities.

1.2 OBJECTIVES

Identify the changing trend of people’s destination across different pandemic phases. Identify how the pandemic influences the types of urban areas that people visit most.

1.3 DATA INTRODUCTION

There are two main datasets used in this project. Firstly, the orgin-destination (OD) dataset is published by the Land Transport Authority at their Datamall. It contains a varaiety of information about transportation patterns at a high spatial and temporal level of detail from January 2020 to Feburary 2021. The second dataset will be using is the Master Plan 2019 Land Use downloaded from Department of Singapore, which includes the geographic location and coordinates of each MRT station. Combining these two datasets together will facilitate spatial analysis.

2 Data Preprocessing

2.1 DATA WRANGLING

2.2 LAND USE CLASSIFICATION

Station locations follow urban planning principles. Land use of the station surrounding area can illustrate the urban functions it serves, its user group and people’s travel behaviors. Therefore, we try to use the proportion of different types of land sue to classify stations into several typologies, and to explore how people’s travel destinations change with pandemic phases.

We create a 700 meters buffer zone for each station since its a suitable walking distance within 10 minutes. Further, we intersect Singapore 2019 land use map and stations wtih 700-meter buffer and figure out the proportion of different types of land use surrounding each station.

The land use distribution varies a lot among different rail stations. To standardize the land use classification, we identify 9 station typologies based on the proportion of different land use.

This figure illustrate different types land use in the surrounding area each rail stations. We need to further calculate the proportion of each type of land use for each station.

All rail stations are classified into different land use typologies according to their land use profile. Some stations have multiple typologies like CC2 (commercial, open space), CC25 (business, public facilities), PW2 (public facilities, open space), etc. We didn’t try to restrict each station to one typology, since the diverse identity can make our analysis more accurate.

The typologies of rail stations are joined to od data so we can further explore how people’s travel destination change according to different station typology in different pandemic phases.

3.1 The Trend of Rail Passenger Volume during the Pandemic

According to policies from Singapore government, we identify three phases of pandemic: pre pandemic (January 2020 - March 2020), Circuit Breaker (April 2020 - June 2020), and reopening (July 2020 onwards).

To get a general idea about our people’s travel behaviou change during the pandemic, we first calculate the total rail passenger volume on weekdays and weekends/holiday eadh month.

Therefore, the influence of the breakout of pandemic is sharp and enormous while the recovery process is slow. During the pandemic, no matter in weekdays or weekends/holidays, people’s activities were, actively or passively, minimized. But people’s commuting demand still exists. We speculate that the travel behaviors happened during the circuit breaker phase were essential while the increased number of travel behaviors happened in pre-pandemic and Reopening were relatively nonessential, which can consider as the travel happened based on ‘attractive’ factors.

3.3 Popularity of Different types of Rail Station

Introducing land use typology to analyze what types of land use are essential to people, and what types of land use are attractive to people.

Generally, passenger volume during weekdays are higher than during weekends/holiday. Passenger volume showed a sharp decrease from March 2020 to April 2020, when Singapore started to implement Circuit Breaker. May 2020 had the lowest passenger volume. Then passenger volume started to increase with weekday growing faster than weekends. After October the passenger volume are relatively stable despite a few fluctuations.

3.2

Zooming in to see the distribution of popularity, Figure 4.2.1 and Figure 4.2.2 shows the popularity of each rail station from January 2020 to February 2021. Overall, the central region influenced by the pandemic the most and even in February 2021, the passenger volumes still did not back to the pre-pandemic level. Similarly, Jurong East, Woodlands and Changi Airport also experienced a sharp decrease and gradual increase during the past 14 months.

The boxplot indicates the popularity of different typologies of rail stations in three phases. The median indicates the average of passenger volume. Overall, Residential with Town Center is the most popular typology in every phase while Reserve typology is the least popular one. The passenger volumes fo each typology all experience a decrease in the circuit breaker phase with Commercial decreased the most. In the reopening phase, the passenger volume of Business typology and Residential typology almost backed to the pre-pandemic level while the passenger volume of Open Space and Public Facilities still kept a relatively low level.

3.4 The Variation of Passenger Volume in Different Types of Rail Station

It is noted that there is a large decrease in variation of business from weekdays to weekends indicated by the low median value compared to other land uses. The main reason could be the declining use of MRT for commuting . The interquartile range reflects the variation in popularity between weekdays and weekends. Residential and residential with town center show little variation, which may be led by the stable daily routines and activities and use of MRT near passengers’ home. Public Facilities also present distinct outlier, and the possible reason could be the increasing traveling during weekends which lead passengers to places where located far away like Changi Airport.

This plot presents that there is an increase in popularity from weekday to weekend in the use of MRT stations in residential with town center and commercial areas before the pandemic. The reason could be that people who need to work from Monday to Friday tend to spend time shopping and go to town center on weekends. During the circuit breaker, the changes in variation were shrunk for all typologies, which was due to the circuit breaker measures including closure of all schools and non-essential workplaces and restrictions on movement and gatherings Furthermore, during the reopening stage, MRT station in residential with town center experience the greatest increase in use from weekday to weekend, and residential, public facilities, commercial and business show similar amount of variation.

The variation of all MRT station typologies decreases from pre pandemic to circuit breaker. The mean value of commercial is relatively low compared to other typologies, indicating the declining use of MRT close to shopping mall where used to be crowded with high flow of people prior to the pandemic. The variation of MRT station in residential area is relatively higher although it is decreasing, it was probably due to people choose to move around their residences to purchase necessities in those uncertain times.

3.5 Spatial Variation of Passenger Volume Variation during Different Pandemic Phases

The analysis of commuter pattern from the period of prepandemic to circuit breaker indicates a relatively higher variation in the residential, residential with town center, commercial and Business typologies. This variation analysis draws to a conclusion that the significant change in ridership pattern after the circuit breaker to residential MRT typologies might have been the result of increasing safety regulations and work from home implementations since the pandemic outbreak. Additionally, commercial typologies largely concentrated into the central region, which can also explain why the central region suffered the most in the pandemic.

The median illustrates higher increase in the variation in popularity of commercial areas, open spaces, and others from circuit breaker to reopening phrase, while the variation in business areas is relatively low. The reason could be the reopening status of different land uses in Phase One and Phase Two after June, 2020. Business first recovered from the Circuit Breaker from 2nd June 202, while pert of commercial activities and open spaces gradually reopened after 19th June. Most of them reopened in July, 2020. On the other hand, besides others typology, the interquartile range of commercial vary to a great extent. There are some typologies showing notable outliers. For example, the outliers of open space are possibly resulted from the different reopening status and the development of each open space. Additionally, the outlier of public facilities is mainly caused by the reopening of transit systems such as flights.

4 Conclusion

4.1 General Conclusion

This map ndicates an increased positive variation in the residential typology, especially in Punggol area. At the same time, commercial and business activities began to recover, which had positive impact on Marina Bay and the surrounding areas. There is a outlier of White typology with sharply increased passenger volume, which may also contributed to its location that near the waterfront or other unclear reason.

(1) The influence of breakout of pandemic is sharp while the recovery process is slow

The passenger volume in each rail station experienced a dramatic decrease in April and the central region, where the passenger volume most concentrated, suffered the most. However, the recovery process is much slower. After the reopening in July, the passenger volume increased gently and in February 2021, the volume still did not return to the pre-pandemic level due to possible reasons such as switching to work-from-home mode.

(2) Rail stations located in Residential, Residential with town center, and Open space are more popular

For the first time period from pre pandemic to circuit breaker between January and June 2020, rail stations in Residential areas witnessed higher passenger volume compared to other typologies while there was a significant decline in the use of rail stations in Commercial areas. The second period between circuit breaker and reopening phases till Feb, 2021, it was noted that the passenger volume variations are relatively high in stations with Residential, Residential with town center, and Open space. People tend to travel more frequently to places near their dwellings rather than long-distance trips in daily life. In addition, they seem to value the opportunities for open spaces after they experienced restricted quarantine measures during circuit breaker.

(3) The pandemic greatly influenced the place people work

The variation of weekday and weekend in passenger volume changed dramatically from pre-pandemic to circuit breaker, the shrunk in variation indicates that people travel less in workdays. The shrunk in variation is most significant in Town Center, Commercial areas, as those areas gather a large number of office jobs, we can perceive people that worked there were working from home during the pandemic. Whereas the shrunk in variation of Business stations are relatively small, suggesting that manufactory, industrial jobs still need workers to work on-site. Additionally, as the Commercial and White types of stations are largely concentrated into the central region, we can conclude that there is a shifting trend of people working in concentrated CBD toward their individual homes.

4.2 Limitations

The project has some scope of limitations in terms of data acquisition and data analysis. For instance, the current land use is not in Singapore’s government database therefore we adopt the Master Plan 2019 land use layer that represents the future land use, thus led to bias of some undeveloped stations. Moreover, there might be other unaccounted factors affecting the passenger volume of a station and our analysis could be improved.